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Multi- and hyperspectral sensors in the visible to short-wave infrared (0.4–2.5 μm) are sensitive to spectral features caused by electronic charge transfer and transition metal crystal field band as well as molecular overtone absorptions. This chapter reviews several processing techniques used to map materials on planetary surfaces based on their reflectance spectra in this spectral region. Techniques that are reviewed include spectral matching in the form of spectral angle and spectral information divergence, linear and nonlinear spectral unmixing, partial unmixing/matched filters, and machine learning approaches in the form of self-organizing maps, neural network classification, and support vector machines.
Multispectral imaging – the acquisition of spatially contiguous imaging data in a modest number (~3–16) of spectral bandpasses – has proven to be a powerful technique for augmenting panchromatic imaging observations on Mars focused on geologic and/or atmospheric context. Specifically, multispectral imaging using modern digital CCD photodetectors and narrowband filters in the 400–1100 nm wavelength region on the Mars Pathfinder, Mars Exploration Rover, Phoenix, and Mars Science Laboratory missions has provided new information on the composition and mineralogy of fine-grained regolith components (dust, soils, sand, spherules, coatings), rocky surface regions (cobbles, pebbles, boulders, outcrops, and fracture-filling veins), meteorites, and airborne dust and other aerosols. Here we review recent scientific results from Mars surface-based multispectral imaging investigations, including the ways that these observations have been used in concert with other kinds of measurements to enhance the overall scientific return from Mars surface missions.
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